Interference is a factor as important as noise in a wireless communication environment. For example, interference from a neighbor cell in a cell boundary, interference from other users concurrently accessing the same frequency band in the same cell, and interference between different data streams when a multiple-input, multiple-output (MIMO) system sends multiple data to a single user not only deteriorate a reception performance of a receiver but also degrade a system capacity.
There are two major methods for the efficient interference cancellation.
One method is a linear interference cancellation such as Minimum Mean Square Error (MMSE) and Zero Forcing (ZF). The linear interference cancellation features the low complexity by linearly canceling the interference by multiplying the received signal by an adequate weight.
Another method is a non-linear interference cancellation such as Serial Interference Cancellation (SIC) and Parallel Interference Cancellation (PIC). The non-linear interference cancellation detects a signal without considering the interference, regenerates the interference signal using the detected signal and a channel coefficient, removes the regenerated interference signal from the received signal, and then redetects the signal. Compared to the linear interference cancellation, the non-linear interference cancellation has the high complexity and the better performance. In specific situations, it is known that the non-linear interference cancellation is optimal in terms of information theory.
The non-linear interference cancellation is divided to two methods based on how to regenerate the interference signal.
One method regenerates the interference using a signal passing through only a detector, and the other method regenerates the interference using a signal passing through up to a decoder. While the latter method can regenerate the more accurate interference signal, its latency is increased.
Typically, a Forward Error Correction (FEC) coding scheme is used as the alternative method to raise reliability of a radio channel. A transmitter sends information data by adding redundancy using a FEC code, and a receiver corrects error merely with the received data. The more amount of the redundancy information, the more amount of the correctable error. Instead, the amount of data transmittable using the same resource is reduced.
Currently, a turbo code and a Low Density Parity Check (LDPC) code, which are known as among the best FEC codes, employ an iterative decoder in the receiver. To decode two codes generated by two encoders, the turbo coding iteratively exchanges respective information and the LDPC coding iteratively exchanges information between a variable node and a check node, to thus maximize the error-correction capability. As the number of the iterations increases, the latency and the complexity increase but the error correction capability is enhanced.
FIG. 1 illustrates a conventional receiver structure using the SIC.
The receiver of FIG. 1 includes a MIMO detector 100, a decoder 102, a hard decision part 104, an interference signal generator 106, a subtracter 108, a MIMO detector 110, a decoder 112, and a hard decision part 114. Hereafter, it is assumed that x1 is an interference signal and x2 is a desired signal to receive.
The MIMO detector 100 outputs an estimated interference signal {circumflex over (x)}1 by demodulating a received signal, y, received on a plurality of antennas according to a predetermined MIMO detection scheme. The decoder 102 decodes the estimated interference signal output from the MIMO detector 100 using a certain demodulation scheme. The hard decision part 104 outputs decoded data by hard-deciding soft values output from the decoder 102, while the soft values are information bits, each with an estimated degree of certainty.
The interference signal generator 106 generates an interference signal h1{tilde over (x)}1 with the decoded data output from the hard decision part 104 and channel information. The subtracter 108 removes the interference signal of the interference signal generator 106 from the received signal y.
The MIMO detector 110 outputs an estimated desired signal {circumflex over (x)}2 by demodulating the interference-free signal output from the subtracter 108 using a certain MIMO detection scheme. The decoder 112 decodes the estimated desired signal fed from the MIMO detector 110 using a certain decoding scheme. The hard decision part 104 outputs decoded data {tilde over (x)}2 by hard-deciding soft values from the decoder 112.
As discussed above, according to the non-linear interference cancellation, the performance with the decoding process is better than the performance without the decoding process. However, since it takes a considerable time to generate the interference signal as shown in FIG. 1, the latency is likely to increase until the desired signal is decoded. Particularly, when the iterative decoding is used as in the turbo coding or the LDPC coding, the latency is deteriorated to thus degrade the entire system performance.